Senior Data Scientist

Contenu de l'offre Senior Data Scientist chez IHS Markit

Paris (75)

Description of Duties

The Automotive Supply Chain and Technology (SCT) team at IHS Markit is in search of a Senior Data Scientist to support its global team's ongoing research and analysis efforts. The research team produces granular forecast datasets on technology, supply chain and the vehicle ecosystem with topics ranging from Connected Car forecasts to Lightweighting, etc.

The Senior Data Scientist will be:

A Coach who mentors our small data science team on best practices, whilst initially not having direct managerial responsibility “Someone in the know”, providing statistical and mathematical concepts and expertise to be applied to an evolving set of requirements to reflect the significant change happening in the automotive industry. Supports relevant stakeholders through quantitative analytics “Get your hands dirty”. Conceives, implements and/or oversees the implementation of appropriate advanced analytics to support SCT team key product initiatives, up until these are productized. Tackle complex problems in the automotive supply chain and technology space using a range of ML and data analysis methods, workflow software (e.g. Knime) in combination with more traditional coding (e.g. Python), Proof of Concept creation and initial validation. Foster a culture that constantly raises the bar for us and others and supports the freedom to explore and innovate. “Deliver results”. Work directly with the heads of research domains, the head of the business line, and the product management team. Influence them with compelling product ideas based on data insights that can move the dial on our business.

Responsibilities and duties

Research, design, implement and deploying full-stack scalable data analytics leveraging in-house data and other sources to support 1) new forecasting products, 2) quality enhancement 3) increased automation levels Drive simultaneous Data Science projects creating and tracking key milestones with various business and data science stakeholders Creation of proof of concepts with clear documentation which can be productised Creation of workflows in the likes of KNIME and other data science workflow tools In some instances be involved in data restructuring and transformation for large inter-connected data sets Implement best practices for the methodology and process of project discovery, data extraction, experimentation, validation, modelling and delivery Build/maintain ETL infrastructure

Qualifications and skills

5+ years’ experience as a data scientist and managing data science projects, having worked on strategy or full-life cycle data science. Experience working with data mining tools such as SPSS, Python, SAS combined with predictive modelling (linear and non-linear regression, time series analysis models, etc) is a requirement. Proven experience with SQL and NoSQL databases like Oracle DB, SQL Server, MongoDB, MySQL Familiarity with data science platforms such as KNIME is a must Experience in managing other data scientists a bonus At minimum, a Degree in Computer Science, Statistics, Applied Math or related quantitative field with proven work experience in the data operations/scientist field Ability to translate technical jargon into layman’s terms and vice-versa Familiar with techniques to manage large databases, including partitioning, compression and indexes as well as data mining Ability to build models (e.g. Linear regression, logistic, Markov models) and use one or more machine learning library/frameworks (e.g. Scikit-learn) with a view to solve complex high dimensional data Hands on experience with data visualisation tools such as Power BI and Tableau Knowledge of OLAP and ETL processes Good communication skills, collaborative team spirit, curiosity to constantly keep thinking of unique approaches and solutions Ability to work independently and think laterally Experience committing to deadlines whilst multi-tasking

What we Offer

Attractive benefits package (Medical services, Special discounts for gyms, Meal vouchers) Ongoing Education (Participation in conferences and training) Access to the most interesting information technologies Work from home & Flexible Working Hours The ability to implement your own ideas and solutions Three days for charity/volunteering Chillout & fun room (pool tennis, PlayStation) Fruit days, Coffee, tea, chocolate Parking Place

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Current Colleagues

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